Papers with Code 아카이브
Temporal Action Localization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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Temporal Action Localization aims to detect activities in the video stream and output beginning and end timestamps. It is closely related to Temporal Action Proposal Generation.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/nlpkeg/D4S
공식 코드Reasons and Solutions for the Decline in Model Performance after Editing
https://github.com/nntanaka/Fourier-Analysis-for-Skeleton-based-Action-Recognition
공식 코드https://github.com/noboevbo/ehpi_action_recognition
공식 코드Simple yet efficient real-time pose-based action recognition
https://github.com/oliverhxh/skeletongcl
공식 코드Graph Contrastive Learning for Skeleton-based Action Recognition
https://github.com/olivesgatech/gradtrust
공식 코드Counterfactual Gradients-based Quantification of Prediction Trust in Neural Networks
https://github.com/oliviazwy/dcgcn
공식 코드Dynamic Compositional Graph Convolutional Network for Efficient Composite Human Motion Prediction
https://github.com/ombretta/videobagnet
공식 코드Video BagNet: short temporal receptive fields increase robustness in long-term action recognition
https://github.com/opanhw/FiNE
공식 코드Precise Localization of Memories: A Fine-grained Neuron-level Knowledge Editing Technique for LLMs
https://github.com/opanhw/MM_Neurons
공식 코드Finding and Editing Multi-Modal Neurons in Pre-Trained Transformers
https://github.com/opendilab/smartrefine
공식 코드SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion Prediction
https://github.com/opendrivelab/end-to-end-autonomous-driving
공식 코드https://github.com/opengvlab/hulk
공식 코드Hulk: A Universal Knowledge Translator for Human-Centric Tasks
https://github.com/opengvlab/humanbench
공식 코드Hulk: A Universal Knowledge Translator for Human-Centric Tasks
https://github.com/opengvlab/internvideo
공식 코드InternVideo: General Video Foundation Models via Generative and Discriminative Learning
https://github.com/opengvlab/internvideo2
공식 코드InternVideo2: Scaling Foundation Models for Multimodal Video Understanding
https://github.com/opengvlab/video-mamba-suite
공식 코드Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding
https://github.com/openmotionlab/motiongpt
공식 코드https://github.com/ostadabbas/video-based-infant-action-recognition
공식 코드Challenges in Video-Based Infant Action Recognition: A Critical Examination of the State of the Art
https://github.com/osvai/ske2grid
공식 코드Ske2Grid: Skeleton-to-Grid Representation Learning for Action Recognition
https://github.com/outsiders17711/e2eet-skeleton-based-hgr-using-data-level-fusion
공식 코드Real-Time Hand Gesture Recognition: Integrating Skeleton-Based Data Fusion and Multi-Stream CNN
https://github.com/ouxiang-li/speed
공식 코드SPEED: Scalable, Precise, and Efficient Concept Erasure for Diffusion Models
https://github.com/p0werHu/articulated-objects-motion-prediction
공식 코드Predicting Long-Term Skeletal Motions by a Spatio-Temporal Hierarchical Recurrent Network
https://github.com/paddlepaddle/paddlevideo
공식 코드A Survey on Video Action Recognition in Sports: Datasets, Methods and Applications
https://github.com/paolomandica/hysp
공식 코드HYperbolic Self-Paced Learning for Self-Supervised Skeleton-based Action Representations
https://github.com/park-jungin/dualpath
공식 코드https://github.com/patrickrperrine/comp-choreo
공식 코드KP-RNN: A Deep Learning Pipeline for Human Motion Prediction and Synthesis of Performance Art
https://github.com/pedro-dm-gomes/agar
공식 코드AGAR: Attention Graph-RNN for Adaptative Motion Prediction of Point Clouds of Deformable Objects
https://github.com/pengxuanyang/uncad
공식 코드UncAD: Towards Safe End-to-end Autonomous Driving via Online Map Uncertainty
https://github.com/pha123661/SA-DVAE
공식 코드https://github.com/phil-bergmann/tracking_wo_bnw
공식 코드https://github.com/pic4ser/act
공식 코드Action Transformer: A Self-Attention Model for Short-Time Pose-Based Human Action Recognition
https://github.com/pic4ser/mpose2021
공식 코드Action Transformer: A Self-Attention Model for Short-Time Pose-Based Human Action Recognition
https://github.com/pic4sercentre/mpose2021
공식 코드Action Transformer: A Self-Attention Model for Short-Time Pose-Based Human Action Recognition
https://github.com/piergiaj/mlb-youtube
공식 코드https://github.com/piergiaj/representation-flow-cvpr19
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.